Minimizing inventory cost in supply chain management has becoming important research field in supply chain area. One of the researches is space utilization when loading the logistics inside the container. Inefficient container loading could result an unnecessary additional costs. For instance, Parcel Delivery Company receives different boxes with different shapes and sizes every single day. In that case, the way how to stack the parcel boxes inside the container are not same for every day and become unpredictable. Many research papers tried to solve this problem theoretically using both exact and heuristic algorithms, (Bortfeldt & Wäscher, 2013). In this paper, authors are trying to address these unpredictable scenarios and propose a new approach that can handle this situation in real life.
In the proposed solution, measurement is the key important part of the solution. In the beginning, the new system will measure the size: width, height and depth of packaging boxes in real time using depth camera. When the system recognized available boxes with their size, the data will be processed for the next purpose. Problem arises when boxes are going to be loaded into the container. What is the best way to stack the heterogeneous boxes inside the container so that wasted spaces are minimized? With placing the depth camera to scan the container environment, system will know the real-time condition of the container, and the dimensions of the coming boxes and then calculate the best way to stack after the camera learned the environment.

Minimizing inventory cost in supply chain management has becoming important research field in supply chain area. One of the researches is space utilization when loading the logistics inside the container. Inefficient container loading could result an unnecessary additional costs. For instance, Parcel Delivery Company receives different boxes with different shapes and sizes every single day. In that case, the way how to stack the parcel boxes inside the container are not same for every day and become unpredictable. Many research papers tried to solve this problem theoretically using both exact and heuristic algorithms, (Bortfeldt & Wäscher, 2013). In this paper, authors are trying to address these unpredictable scenarios and propose a new approach that can handle this situation in real life.

In the proposed solution, measurement is the key important part of the solution. In the beginning, the new system will measure the size: width, height and depth of packaging boxes in real time using depth camera. When the system recognized available boxes with their size, the data will be processed for the next purpose. Problem arises when boxes are going to be loaded into the container. What is the best way to stack the heterogeneous boxes inside the container so that wasted spaces are minimized? With placing the depth camera to scan the container environment, system will know the real-time condition of the container, and the dimensions of the coming boxes and then calculate the best way to stack after the camera learned the environment.